Agent-based crypto policy simulation platform for stress-testing regulations
DFL24‑Sim lets regulators model retail trader behavior, market dynamics, and policy rules, then runs large‑scale agent simulations to evaluate friction effects and adversary evasion. It includes calibrated behavioral models, network generation, and sensitivity analysis tools. Designed for fintech labs and policymakers to pre‑test interventions before field trials, offering deeper insight than simple rule‑based checks.
View on GitHub →DFL24-Tech/Crypto-Consumer-Protection-Policy-Simulation